基于维纳滤波的矿井监控图像的复原技术
Recovery Technology of Mine Monitoring Image Based on Wiener Filtering
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摘要: 结合煤矿井下环境的实际特点和煤矿监控图像的需求,研究了煤矿井下监控图像的理论复原理论,提出了矿井监控图像的维纳滤波复原法,并利用基于二次模糊的模糊度评价算法进行评价。通过MATLAB软件对煤矿井下综采工作面的监控图像的复原效果进行验证,得到在高斯模糊的标准差σb=0.6,维纳滤波信噪比K=0.055时,煤矿井下综采工作面的监控图像的复原效果最佳。Abstract: Combined with the actual characteristics of coal mine underground environment and the demand of coal mine monitoring image, this paper studies the theory of restoration theory of monitoring image in coal mine. We propose Wiener filtering restoration method for mine monitoring image, and use fuzzy evaluation algorithm based on secondary fuzzy to carry on evaluation. In this paper, MATLAB software is used to verify the restoration effect of monitoring images in fully mechanized coal mining face to obtain that the the coal mine fully mechanized face monitoring image recovery effect is best when the standard deviation of Gauss fuzzy is 0.6, Wiener filter SNR K is 0.055.